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Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions

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  • Benkhelifa, Lazhar

Abstract

In this paper, we generalize the classical estimator of the reinsurance premium for heavy-tailed loss distributions with a kernel-type estimator. Since this estimator exhibits a bias, we propose its bias-reduced version by using a least-squares method. The asymptotic normality of the proposed estimators is established under suitable assumptions. A small simulation study is carried out to prove the performance of our approach.

Suggested Citation

  • Benkhelifa, Lazhar, 2014. "Kernel-type estimator of the reinsurance premium for heavy-tailed loss distributions," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 65-70.
    • Handle: RePEc:eee:insuma:v:59:y:2014:i:c:p:65-70
    DOI: 10.1016/j.insmatheco.2014.08.006
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    References listed on IDEAS

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    5. Vandewalle, B. & Beirlant, J., 2006. "On univariate extreme value statistics and the estimation of reinsurance premiums," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 441-459, June.
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